CN111869210B - Deriving Dynamic Range Adjustment (DRA) parameters for video coding - Google Patents

Abstract

Dynamic range adjustment may be used to correct for distortion that may occur when the dynamic range of colors in a video is transformed. In various examples, dynamic range adjustment may be performed using a non-interruptive function having a series of color values as input. Parameters describing the function may be encoded into the bitstream and these parameters may be used by the decoding process to reconstruct the function. The function may be linear or non-linear. The function optionally comprises a piecewise linear function.

Description

Deriving Dynamic Range Adjustment (DRA) parameters for video coding

Cross Reference to Related Applications

This patent application claims priority from provisional application No. 62/647,472 entitled "DERIVING DYNAMIC RANGE ad just (dra) PARAMETERS FOR VIDEO CODING" filed on day 3, month 23, 2018 and non-provisional application No. 16/360,971 entitled "DERIVING DYNAMIC RANGE ad just (dra) PARAMETERS FOR VIDEO CODING" filed on day 21, month 3, 2019 and assigned to its assignee and is hereby expressly incorporated herein by reference.

Technical Field

The present application relates to video systems and methods. For example, the present application relates to the field of encoding of video signals having a High Dynamic Range (HDR) and Wide Color Gamut (WCG) representation. The present application specifies the signaling and operations to be applied to video data in a particular color space to achieve more efficient compression of HDR and WCG video data. Benefits of the subject matter of this application include improving compression efficiency of a hybrid-based video coding system for encoding HDR and WCG video data.

Background

Examples of Video Coding standards include ITU-T H.261, ISO/IEC MPEG-1Visual, ITU-T H.262 or ISO/IEC MPEG-2Visual, ITU-T H.263, ISO/IEC MPEG-4Visual, and ITU-T H.264 (also known as ISO/IEC MPEG-4AVC), including their Scalable Video Coding (SVC) and Multiview Video Coding (MVC) extensions. In addition, a Video Coding standard, High Efficiency Video Coding (HEVC), has been developed by Joint Collaboration Video Coding (JCT-VC) of the ITU-T Video Coding Experts Group (VCEG) and the Video Coding Joint Collaboration Group (MPEG) of the ISO/IEC Moving Picture Experts Group (MPEG). The latest draft of the HEVC specification, namely "recommendation ITU-T H.265: High Efficiency Video Coding (HEVC)", may be found inhttp:// www.itu.int/rec/T-REC-H.265-201504-I/enAnd (4) obtaining. In addition to improving coding efficiency, there is a need for video codecs to further support HDR and WCD representations.

Disclosure of Invention

In various embodiments, systems (such as encoding and decoding devices), methods, and computer-readable media for encoding and decoding video data are provided.

One embodiment includes a method of encoding video data, the method including obtaining video data at an encoding device. For a portion of a video picture of video data, the video data includes parameters that describe a function of uninterrupted, quantized parameters. The function defines a dynamic range adjustment of the color in the portion of the video frame. A quantization factor is associated with the portion of the picture. The method also includes generating a syntax structure indicating the parameters and generating encoded video data from the video data. The syntax structure is included within the encoded video data.

One embodiment includes a method of decoding video data. The method includes determining, from an encoded video bitstream comprising encoded video data, for a portion of a video picture from the encoded video data, a syntax structure comprising parameters describing a non-interruptive function of quantization parameters, the function being non-interruptive for dynamic range adjustment of colors in the portion of the video picture. A quantization factor is associated with the portion of the picture. The method also includes decoding the video picture using the encoded video data and applying the function to samples in the portion of the video picture to perform dynamic range adjustment.

Another embodiment comprises an apparatus for encoding video data. The apparatus includes a video processor and a memory configured to store at least a portion of a video picture. The video processor is configured to obtain video data, and for a portion of a video picture of the video data, the obtained video data includes parameters that describe a function of the uninterrupted, quantization parameter. The function defines a dynamic range adjustment of colors in a portion of a video frame. A quantization factor is associated with the portion of the picture. The video processor is further configured to generate a syntax structure indicating the parameters and generate encoded video data from the video data. The syntax structure is included within the encoded video data.

Another embodiment comprises an apparatus for decoding video data. The apparatus includes a video processor and a memory configured to store at least a portion of a video picture. The video processor is configured to determine, from an encoded video bitstream comprising encoded video data, for a portion of a video picture from the encoded video data, a syntax structure comprising parameters describing a function of a quantization factor, the function being an uninterrupted dynamic range adjustment for colors in the portion of the video picture. A quantization parameter is associated with the portion of the picture. The processor is also configured to decode the video picture using the encoded video data and apply the function to samples in the portion of the video picture to perform dynamic range adjustment.

Another embodiment comprises a method for decoding video data. The apparatus comprises means for storing at least a portion of a video picture and means for processing video data. The apparatus for processing video data includes means for determining, from an encoded video bitstream comprising encoded video data, for the portion of a video picture from the encoded video data, a syntax structure comprising parameters describing a function of quantization parameters, the function being uninterrupted for dynamic range adjustment of colors in the portion of the video picture. A quantization parameter is associated with the portion of the picture. The means for processing video data also includes means for decoding a video picture using the encoded video data, and means for applying the function to samples in a portion of the video picture to perform dynamic range adjustment.

Another embodiment comprises an apparatus for encoding video data. The apparatus comprises means for storing at least a portion of a video picture and means for processing video data. The means for processing video data comprises means for obtaining video data, and for a portion of a video picture of the video data, the obtained video data comprises parameters that describe a function of the uninterrupted, quantization parameter. The function defines a dynamic range adjustment of colors in a portion of a video frame. A quantization factor is associated with the portion of the picture. The means for processing video data further comprises means for generating a syntax structure indicating the parameters and means for generating encoded video data from the video data. The syntax structure is included in the encoded video data.

Another embodiment includes a non-transitory computer-readable medium having instructions stored thereon that, when executed, cause a processor. The instructions also cause the processor to obtain video data, and for a portion of a video picture of the video data, the obtained video data includes parameters that describe a function of the uninterrupted, quantization parameter. The function defines a dynamic range adjustment of colors in a portion of a video frame. A quantization factor is associated with the portion of the picture. The instructions also cause the processor to generate a syntax structure indicating the parameters and generate encoded video data from the video data. The syntax structure is included within the encoded video data.

Another embodiment includes a non-transitory computer-readable medium having instructions stored thereon that, when executed, cause a processor to store at least a portion of a video picture and a video processor. The instructions also cause the processor to determine, from an encoded video bitstream comprising the encoded video data, for a portion of a video picture from the encoded video data, a syntax structure comprising parameters describing a function of a quantization factor, the function being an uninterrupted, dynamic range adjustment for colors in the portion of the video picture. The quantization parameter is associated with a portion of a picture. The instructions also cause the processor to decode a video picture using the encoded video data and apply the function to samples in the portion of the video picture to perform dynamic range adjustment.

Drawings

Fig. 1 includes a block diagram illustrating a system including an encoding device and a decoding device;

FIG. 2 illustrates the dynamic range of typical human vision compared to the dynamic range of various display types;

FIG. 3 illustrates an example of a chromaticity diagram;

fig. 4 includes a diagram illustrating an example of a process for transforming (convert) high precision linear RGB video data for the purpose of encoding video data;

fig. 5 includes a diagram illustrating an example of a process for recovering converted HDR video data obtained from a decoded bitstream produced by a decoder;

fig. 6 includes a graph illustrating an example of an illuminance curve generated by a transfer function (transfer function);

fig. 7 includes a graph showing an example of input values to PQ _ TF;

fig. 8 includes a graph illustrating an example of an LCS function;

fig. 9 includes a graph plotting y-values for a range of x-values, showing a comparison of an example of chroma QP offset as a function of input QP and a linear approximation of this correlation.

Fig. 10 includes a graph plotting y-values for a range of values for x, showing a comparison of chroma QP correction to a linear approximation thereof.

Fig. 11 includes a flowchart illustrating an example of a process for encoding video data;

fig. 12 includes a flow chart illustrating an example of a process for decoding video data;

FIG. 13 is a block diagram illustrating an example encoding device; and

fig. 14 is a block diagram illustrating an example decoding apparatus.

Detailed Description

Dynamic Range Adjustment (DRA) can be used to correct for distortions that may occur when the Dynamic Range of colors in a video is transformed. In some forms of the DRA, the parameters and functions applied as part of the DRA may be based on chroma QP terms having integer values that result in a scaling function characterized by discontinuities, such as in the form of a staircase function. These discontinuities may form visually noticeable artifacts.

In various examples, the DRA may be performed using a non-interruptive function having as input a series of color values or samples. Such functions may include logarithmic functions of DRA components derived from integer QP parameters to avoid discontinuities in the DRA function applied. Parameters describing the function may be encoded into the bitstream and these parameters may be used by the decoder to reconstruct a continuous function. Such a function may be linear or non-linear. Such a function may be defined as a piecewise function or otherwise defined such that the function is uninterrupted.

Dynamic range adjustment may be used to improve the compression efficiency of video data. For example, the process may be performed at an encoding device that transforms video data into a format more suitable for compression, such that fewer bits may be required to encode the video data without affecting the quality of the decoded video data. The reverse process may be performed at a decoding device that converts the data back to the same format as the input video data.

Dynamic range adjustment may also be used to transform video data into a representation suitable for a particular type of display. The characteristics of the display into which the representation may be transformed may include, for example, the peak luminance (luminance) of the display, the dynamic range of the display, the color gamut of the display, and/or the primary colors used by the display. In some examples, dynamic range adjustment may be used to transition video data from SDR to HDR, and vice versa, as the case may be.

Referring to fig. 1, a video source 102 may provide video data to an encoding device 104. The video source 102 may be part of a source device or may be part of a device other than a source device. The video source 102 may include a video capture device (e.g., a video camera, a camera phone, a video phone, etc.), a video archive containing stored video, a video server or content provider providing video data, a video feed interface receiving video from the video server or content provider, a computer graphics system for generating computer graphics video data, a combination of these sources, or any other suitable video source.

The video data from the video source 102 may include one or more input pictures or frames. A picture or frame of video is a still image of a scene. The encoder engine 106 (or encoder) of the encoding device 104 encodes the video data to generate an encoded video bitstream. In some examples, an encoded video bitstream (or "video bitstream" or "bitstream") is a series of one or more encoded video sequences. A Coded Video Sequence (CVS) comprises a series of Access Units (AUs) starting from an AU having a random access point picture and having specific properties at the base layer up to and including a next AU having a random access point picture and having specific properties at the base layer. For example, a particular property of a random access point picture that initiates CVS may include a RASL flag equal to 1 (e.g., NoRaslOutputFlag). Otherwise, the random access point picture (with RASL flag equal to 0) will not initiate CVS. An Access Unit (AU) includes one or more encoded pictures and control information corresponding to the encoded pictures sharing the same output time. Coded slices (slices) of a picture are encapsulated at the bitstream level into data units called Network Abstraction Layer (NAL) units. For example, an HEVC video bitstream may include one or more CVSs that contain NAL units. Each of the NAL units has a NAL unit header. In one example, the header is one byte for h.264/AVC (except for multi-layer extensions) and two bytes for HEVC. Syntax elements in the NAL unit header take on designated bits and are therefore visible to all kinds of systems and Transport layers, such as Transport streams, Real-time Transport (RTP) protocols, file formats, etc.

There are two types of NAL units in the HEVC standard, including Video Coding Layer (VCL) NAL units and non-VCL NAL units. A VCL NAL unit includes one slice or slice segment of coded picture data (as described below), and a non-VCL NAL unit includes control information related to one or more coded pictures. In some cases, a NAL unit may be referred to as a packet (packet). An HEVC AU includes VCL NAL units that contain encoded picture data and non-VCL NAL units (if any) corresponding to the encoded picture data.

NAL units may contain bit sequences (e.g., coded video bitstreams, CVSs of bitstreams, etc.) that form coded representations of video data, such as coded representations of pictures in video. The encoder engine 106 generates an encoded representation of the picture by partitioning each picture into a plurality of slices. One slice is independent of the other slices such that information in that slice is encoded without being dependent on data from other slices within the same picture. A slice comprises one or more slices comprising an individual slice, and one or more related slice segments (if present) that are dependent on a previous slice. The slice is then partitioned into Coding Tree Blocks (CTBs) of luminance (luma) samples and chrominance (chroma) samples. The CTB of a luma sample and one or more CTBs of chroma samples and the syntax of these samples are called Coding Tree Units (CTUs). The CTU is the basic processing unit for HEVC coding. The CTUs may be divided into Coding Units (CUs) of different sizes. A CU contains an array of luma samples and an array of chroma samples called Coding Blocks (CBs).

The luminance CB and the chrominance CB may be further divided into Prediction Blocks (PB). PB is a block of samples of luma or chroma components that are inter predicted or intra block copy predicted (when available or enabled for use) using the same motion parameters. The luminance PB and one or more chrominance PB and associated syntax form a Prediction Unit (PU). For inter prediction, a set of motion parameters (e.g., one or more motion vectors, reference indices, etc.) is signaled in the bitstream to each PU and used for inter prediction of luma PB and one or more chroma PBs. The motion parameters may also be referred to as motion information. CBs may also be partitioned into one or more Transform Blocks (TBs). TB denotes a square block of samples of the color component on which the same two-dimensional transform is applied to encode the prediction residual signal. A Transform Unit (TU) represents the TB of luma and chroma samples and the corresponding syntax elements.

The size of a CU corresponds to the size of the coding mode and may be square in shape. For example, the size of a CU may be 8 × 8 samples, 16 × 16 samples, 32 × 32 samples, 64 × 64 samples, or any other suitable size up to the size of the corresponding CTU. The phrase "nxn" is used herein to refer to the pixel dimension (e.g., 8 pixels by 8 pixels) of a video block in both the vertical and horizontal dimensions. The pixels in a block may be arranged in rows and columns. In some examples, the number of pixels of the block in the horizontal direction may be different from the number of pixels in the vertical direction. Syntax data associated with a CU may describe, for example, partitioning the CU into one or more PUs. The partition mode may be different between whether a CU is intra prediction mode encoded or inter prediction mode encoded. The PU may be partitioned into non-squares in shape. Syntax data associated with a CU may also describe partitioning of the CU into one or more TUs, e.g., according to CTUs. The TU may be square or non-square in shape.

As one example, according to the HEVC standard, a transform may be performed using Transform Units (TUs). The TUs may be different for different CUs. The size of a TU may be determined based on the size of a PU within a given CU. The TU may be the same size or smaller than the PU. In some examples, a quadtree structure called a Residual Quadtree (RQT) may be used to subdivide residual samples corresponding to a CU into smaller units. The leaf nodes of the RQT may correspond to TUs. The pixel difference values associated with the TUs may be transformed to produce transform coefficients. The transform coefficients may then be quantized by the encoder engine 106.

Once a picture of video data is partitioned into CUs, encoder engine 106 predicts each PU using prediction modes. The prediction unit or block is then subtracted from the original video data to obtain a residual (as described below). For each CU, the prediction mode may be signaled inside the bitstream using syntax data. The prediction mode may include intra prediction (or intra picture prediction) or inter prediction (or inter picture prediction). Intra prediction exploits the correlation between spatially adjacent samples within a picture. For example, in the case of using intra prediction, each PU is predicted from neighboring image data in the same picture using, for example, DC prediction to find the average of the PU, using planar prediction to fit a planar surface to the PU, using directional prediction to extrapolate from the neighboring data, or using any other suitable type of prediction. Inter-prediction uses temporal correlation between pictures in order to derive motion compensated predictions of blocks of image samples. For example, where inter prediction is used, each PU is predicted using motion compensated prediction from image data in one or more reference pictures (preceding or following the current picture in output order). For example, a decision may be made at the CU level whether to encode a picture region using inter-picture prediction or intra-picture prediction.

In some examples, one or more slices of a picture are assigned a slice type. The slice types include I slice, P slice, and B slice. An I slice (intra frame, independently decodable) is a picture slice that is encoded only by intra prediction, and is therefore independently decodable, since an I slice only requires data within the frame to predict any prediction unit or prediction block of the slice. A P slice (unidirectional predicted frame) is a picture slice that can be encoded with intra prediction and with unidirectional inter prediction. Each prediction unit or block within a P slice is encoded using either intra prediction or using inter prediction. When inter prediction is applied, a prediction unit or a prediction block is predicted by only one reference picture, and thus reference samples are from only one reference region of one frame. A B slice (bi-directionally predicted frame) is a picture slice that can be encoded with intra prediction and with inter prediction (e.g., bi-directional prediction or uni-directional prediction). A prediction unit or prediction block of a B slice may be bi-predicted from two reference pictures, where each picture contributes one reference region, and the sample sets of the two reference regions are weighted (e.g., with equal weights or different weights) to produce a prediction signal for the bi-predicted block. As described above, slices of one picture are independently encoded. In some cases, a picture may be encoded as only one slice.

The PU may include data (e.g., motion parameters or other suitable data) related to the prediction process. For example, when a PU is encoded using intra prediction, the PU may include data describing an intra prediction mode of the PU. As another example, when a PU is encoded using inter prediction, the PU may include data defining a motion vector of the PU. The data defining the motion vector for the PU may describe, for example, a horizontal component (Δ x) of the motion vector, a vertical component (Δ y) of the motion vector, a resolution of the motion vector (e.g., integer precision, quarter-pixel precision, or eighth-pixel precision), a reference picture to which the motion vector points, a reference index, a reference picture list (e.g., list 0, list 1, or list C) of the motion vector, or any combination thereof.

The encoding device 104 may then perform the transformation and quantization. For example, after prediction, the encoder engine 106 may calculate residual values corresponding to the PUs. The residual values may include pixel difference values between a current pixel block (PU) being encoded and a prediction block (e.g., a predicted version of the current block) used to predict the current block. For example, after generating a prediction block (e.g., issuing inter prediction or intra prediction), encoder engine 106 may generate a residual block by subtracting the prediction block produced by the prediction unit from the current block. The residual block comprises a set of pixel difference values that quantify the differences between the pixel values of the current block and the pixel values of the prediction block. In some examples, the residual block may be represented in a two-dimensional block format (e.g., a two-dimensional matrix or array of pixel values). In such an example, the residual block is a two-dimensional representation of the pixel values.

Any residual data that may remain after prediction is performed is transformed using a block transform, which may be based on a discrete cosine transform, a discrete sine transform, an integer transform, a wavelet transform, other suitable transform function, or any combination thereof. In some cases, one or more block transforms (e.g., of size 32 × 32, 16 × 16, 8 × 8, 4 × 4, etc.) may be applied to the residual data in each CU. In some examples, the TUs may be used for the transform and quantization processes implemented by the encoder engine 106. A given CU with one or more PUs may also include one or more TUs. As described in further detail below, the residual values may be transformed into transform coefficients using a block transform, and then may be quantized and scanned using TUs to produce serialized (serialized) transform coefficients for entropy encoding.

In some examples, after intra-prediction or inter-prediction encoding using PUs of the CU, encoder engine 106 may calculate residual data for TUs of the CU. A PU may include pixel data in the spatial domain (or pixel domain). A TU may include coefficients in the transform domain after applying the block transform. As previously described, the residual data may correspond to pixel differences between pixels of the unencoded picture and prediction values corresponding to the PU. The encoder engine 106 may form a TU that includes residual data of the CU, and may then transform the TU to produce transform coefficients for the CU.

The encoder engine 106 may perform quantization of the transform coefficients. Quantization provides further compression by quantizing the transform coefficients to reduce the amount of data used to represent the coefficients. For example, quantization may reduce the bit depth associated with some or all of the coefficients. In one example, during quantization, a coefficient having an n-bit value may be rounded down to an m-bit value, where n is greater than m.

Once quantization is performed, the encoded video bitstream includes quantized transform coefficients, prediction information (e.g., prediction modes, motion vectors, block vectors, etc.), partition information, and any other suitable data, such as other syntax data. Different elements of the encoded video bitstream may then be entropy encoded by the encoder engine 106. In some examples, encoder engine 106 may scan the quantized transform coefficients using a predefined scan order to produce a serialized vector that may be entropy encoded. In some examples, the encoder engine 106 may perform an adaptive scan. After scanning the quantized transform coefficients to form a vector (e.g., a one-dimensional vector), encoder engine 106 may entropy encode the vector. For example, the encoder engine 106 may use context adaptive variable length coding, context adaptive binary arithmetic coding, syntax-based context adaptive binary arithmetic coding, probability interval partition entropy coding, or another suitable entropy coding technique.

As previously described, an HEVC bitstream includes a set of NAL units that includes VCL NAL units and non-VCL NAL units. VCL NAL units include coded picture data that form a coded video bitstream. For example, the bit sequence forming the encoded video bitstream is retransmitted in VCL NAL units. non-VCL NAL units may contain, among other information, parameter sets with high level information related to the coded video bitstream. For example, the parameter set may include a Video Parameter Set (VPS), a Sequence Parameter Set (SPS), and a Picture Parameter Set (PPS). Examples of goals for parameter sets include bit rate efficiency, error recovery capability, and providing a system layer interface. Each slice references a single active PPS, SPS, and VPS to access information that the decoding device 112 may use to decode the slice. An Identifier (ID) may be encoded for each parameter set, including VPS ID, SPS ID, and PPS ID. The SPS includes an SPS ID and a VPS ID. The PPS includes a PPS ID and an SPS ID. Each slice header includes a PPS ID. Using these IDs, the active parameter set can be represented for a given slice.

The PPS includes information applicable to all slices in a given picture. As such, all slices in a picture refer to the same PPS. Slices in different pictures may also refer to the same PPS. The SPS includes information that applies to all pictures in the same Coded Video Sequence (CVS) or bitstream. As previously mentioned, the encoded video sequence is a series of Access Units (AUs) starting from an AU having a random access point picture (e.g., an Instantaneous Decoding Reference (IDR) picture or a Broken Link Access (BLA) picture, or other suitable random access point picture) and having certain properties at the base layer (as described above) up to and including the next AU (or end of the bitstream) having a random access point picture and having certain properties at the base layer. Within an encoded video sequence, the information in the SPS may not be picture specific. Pictures in an encoded video sequence may use the same SPS. The VPS includes information applicable to all layers in the encoded video sequence or bitstream. The VPS includes a syntax structure whose syntax elements apply to the entire encoded video sequence. In some examples, the VPS, SPS, or PPS may be transmitted in-band with the encoded bitstream. In some examples, the VPS, SPS, or PPS may be transmitted out-of-band in a transmission separate from the NAL units containing the encoded video data.

The video bitstream may also include Supplemental Enhancement Information (SEI) messages. For example, the SEI NAL unit may be part of a video bitstream. In some examples, the SEI message may be signaled separately from the video bitstream. In some cases, the SEI message may contain information that is not needed by the decoding process. For example, the information in the SEI message may not be necessary for a decoder to decode a video picture of the bitstream, but the decoder may use the information to improve the display or processing of the picture (e.g., decoded output). The information in the SEI message may be embedded metadata. In one illustrative example, the decoder-side entity may use information in the SEI message to improve the visibility of the content. In some cases, a particular application standard may require the presence of such SEI messages in the bitstream so that improvements in quality can be brought to all devices that conform to the application standard (e.g., frame packing SEI messages carrying a frame compatible monoscopic 3DTV video format (where SEI messages are carried for each frame of the video), processing recovery point SEI messages, using panorama scanning rectangular SEI messages in DVB, and many other examples).

An output 110 of the encoding device 104 may send NAL units constituting encoded video data to a decoding device 112 of the receiving device over a communication link 120. An input 114 of the decoding device 112 may receive NAL units. The communication link 120 may include a channel provided by a wireless network, a wired network, or a combination of wired and wireless networks. The wireless network may include any wireless interface or combination of wireless interfaces and may include any suitable wireless network (e.g., the internet or other wide area network, packet-based network, WiFi, Radio Frequency (RF), UWB, WiFi direct, cellular, Long Term Evolution (LTE), wimax, etc.). The wired network may include any wired interface (e.g., fiber optic, ethernet, power line, ethernet over coaxial cable, Digital Signal Line (DSL), etc.). Wired and/or wireless networks may be implemented using various devices, such as base stations, routers, access points, bridges, gateways, switches, and so forth. The encoded video data may be modulated according to a communication standard, such as a wireless communication protocol, and transmitted to a receiving device.

In some examples, the encoding device 104 may store the encoded video data in the storage 108. The output 110 may retrieve the encoded video data from the encoder engine 106 or from the storage 108. Storage 108 may comprise any of a variety of distributed or locally accessed data storage media. For example, storage 108 may include a hard disk drive, a memory disk, flash memory, volatile or non-volatile memory, or any other suitable digital storage medium for storing encoded video data.

The input 114 of the decoding device 112 receives the encoded video bitstream data and may provide the video bitstream data to a decoder engine 116 or a storage 118 for later use by the decoder engine 116. The decoder engine 116 may decode the encoded video bitstream data by entropy decoding (e.g., using an entropy decoder) and extracting elements of one or more encoded video sequences that make up the encoded video data. The decoder engine 116 may then rescale the encoded video bitstream data and perform the inverse transform. The residual data is then passed to the prediction stage of the decoder engine 116. The decoder engine 116 then predicts a block of pixels (e.g., a PU). In some examples, the prediction is added to the output of the inverse transform (residual data).

The decoding device 112 can output the decoded video to a video destination device, which can include a display or other output device for displaying the decoded video data to a consumer of the content. In some aspects, video destination device 122 may be part of a receiving device that includes decoding device 112. In some aspects, video destination device 122 may be part of a separate device different from the receiving device.

In some examples, the video encoding device 104 and/or the video decoding device 112 may be integrated with an audio encoding device and an audio decoding device, respectively. The video encoding device 104 and/or the video decoding device 112 may also include other hardware or software necessary to implement the above-described encoding techniques, such as one or more microprocessors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), discrete logic, software, hardware, firmware or any combinations thereof. The video encoding device 104 and the video decoding device 112 may be integrated as part of a combined encoder/decoder (codec) in the respective devices. An example of specific details of the encoding device 104 is described below with reference to fig. 13. An example of specific details of the decoding apparatus 112 is described below with reference to fig. 14.

Various criteria are also defined that describe the colors in the captured video, including contrast (e.g., brightness or darkness of pixels in the video), color accuracy, and so forth. For example, color parameters may be used by a display device that is capable of using the color parameters to determine how to display pixels in a video. One example standard from the International Telecommunications Union (ITU), ITU-R recommendation bt.709 (referred to herein as "bt.709"), defines the standard for High-Definition Television (HDTV). The color parameters defined by bt.709 are commonly referred to as Standard Dynamic Range (SDR) and Standard color gamut. Another example standard is the ITU-R recommendation bt.2020 (referred to herein as "bt.2020"), which defines the standard for Ultra-High-Definition Television (UHDTV). The Color parameters defined by bt.2020 are commonly referred to as High Dynamic Range (HDR) and Wide Color Gamut (WCG). The dynamic range and color gamut are collectively referred to herein as color volume.

Next generation video applications are expected to operate with video data representing the captured scenery in HDR and WCG. The parameters of dynamic range and color gamut utilized are two independent attributes of video content, and their specifications for digital television and multimedia services are defined by several international standards. For example, as described above, bt.709 defines parameters for HDTV such as SDR and standard color gamut, and bt.2020 specifies UHDTV parameters such as HDR and wide color gamut. There are also other standards development organization documents that specify these properties in other systems, for example, the P3 color gamut is defined in SMPTE-231-2 and some parameters of HDR are defined in stmtte-2084.

The dynamic range may be defined as the ratio of the minimum luminance (brightness) and the maximum luminance of the video signal. The dynamic range can also be measured in terms of the number of aperture steps (f-stop). For example, in a camera, the number of aperture steps is the ratio of the focal length of the lens to the camera aperture diameter. One aperture level may correspond to twice the dynamic range of the video signal. As an example, MPEG defines HDR content as content characterized by luminance variations over 16 aperture steps. In some examples, the dynamic range between 10 and 16 aperture steps is considered the intermediate dynamic range, but in other examples this is considered the HDR dynamic range. The human visual system is able to perceive a much larger dynamic range, however, the human visual system comprises an adaptive mechanism to reduce the simultaneous range (simulaneous range).

Fig. 2 illustrates the dynamic range of a typical human vision 202 compared to the dynamic range of various display types. FIG. 2 scales logarithmically with nits (e.g., in cd/m) ² Logarithmic scaling) shows the luminance range 200. For example, the starlight is at approximately 0.0001 nit or-4 over the illustrated illumination range 200, and the moonlight is at approximately 0.01 nit (2 over the illumination range 200). Typical room light may be between 1 and 100 nits (0 and 2 over an illumination range 200). The sunlight may be between 10000 nits and 1000000 nits (between 4 and 6 on the illumination range 200).

Human vision 202 is capable of perceiving anywhere between less than 0.0001 nit to more than 1000000 nits, with the precise range varying from person to person. The dynamic range of the human vision 202 includes a simultaneous dynamic range 204. While the dynamic range 204 is defined as the ratio between the highest and lowest illumination values at which an object can be detected while the eye is fully adaptive (full adaptation). Full adaptation occurs when the eye is in a steady state after adapting to the current ambient light conditions or illumination level. Although the simultaneous dynamic range 204 is shown in the example of fig. 2 as being between about 0.1 nit and about 3200 nit, the simultaneous dynamic range 204 may be centered at other points along the luminance range 200 and the width may vary at different luminance levels. Additionally, the simultaneous dynamic range 204 may vary from person to person.

Fig. 2 also shows the approximate dynamic range of SDR display 206 and HDR display 208. SDR displays include monitors, televisions, tablet screens, smartphone screens, and other display devices capable of displaying SDR content. HDR displays include, for example, ultra-high definition televisions and other display devices capable of displaying HDR content.

Bt.709 specifies that the dynamic range of the SDR display 206 may be about 0.1 to 100 nits, or about 10 aperture steps, which is significantly less than the dynamic range of human vision 202. The dynamic range of the SDR display 206 is also less than the simultaneous dynamic range 204 shown. Some video applications and services are restricted by rec.709 and provide SDR, and typically support a luminance (or luminance) range of about 0.1 to 100 nits. SDR displays also do not accurately reproduce nighttime conditions (e.g., starlight, at about 0.0001 nits) or bright outdoor conditions (e.g., about 1000000 nits). However, some SDR displays may support peak luminances greater than 100 nits, and may display SDR content in a range outside of 0.1 to 100 nits.

It is expected that the next generation video service will provide a dynamic range of up to 16 aperture steps. HDR displays can cover a wider dynamic range than SDR displays. For example, an HDR display may have a dynamic range of about 0.01 nit to about 5600 nit (or 16 aperture steps). While HDR displays also do not encompass the dynamic range of human vision, HDR displays may be closer to the simultaneous dynamic range 204 that can cover an average person. Specifications for the dynamic range parameters of HDR displays can be found in, for example, bt.2020 and ST 2084.

A color gamut describes the range of colors available on a particular device, such as a display or printer. The color gamut may also be referred to as the color dimension. Fig. 3 shows an example of a chromaticity diagram 300 overlaid with a triangle representing an SDR gamut 304 and a triangle representing an HDR gamut 302. The values on curve 306 in graph 300 are the color spectrum; that is, color caused by light of wavelengths in the visible spectrum. The colors below the curve 306 are non-spectral: the straight line between the lower points of the curve 306 is called the purple line, and the color inside the graph 300 is an unsaturated color, which is a spectral color or various mixtures of purple and white. The point labeled D65 indicates the location of the white color of the illustrated spectral curve 306. The curve 306, which may also be referred to as a spectral or spectral locus, represents the boundary of a natural color.

The triangle representing SDR color gamut 304 is based on the three primary colors red, green, and blue, provided by bt.709. The SDR color gamut 304 is a color space used by HDTV, SDR broadcasts, and other digital media content.

The triangle representing the wide HDR color gamut 302 is based on the three primary colors red, green and blue provided by bt.2020. As shown in fig. 3, the HDR gamut 302 provides approximately 70% more colors than the SDR gamut 304. Color gamuts defined by other standards, such as the Digital Cinema Initiative (DCI) P3 (referred to as DCI-P3), provide some colors outside the HDR gamut 302, but do not completely encompass the HDR gamut 302. DCI-P3 is used for digital motion projection.

Table 1 shows examples of colorimetry parameters for a selected color space, including those provided by bt.709, bt.2020, and DCI-P. For each color space, table 1 provides the x and y coordinates of the chromaticity diagram.

Table 1: colorimetry parameters of a selected color space

Video data having a large color capacity (e.g., video data having a high dynamic range and a wide color gamut) can be acquired and stored with a high degree of accuracy for each component. For example, floating point values may be used to represent the luminance and chrominance values of each pixel. As a further example, a 4:4:4 chroma format may be used, where the luma, chroma-blue, and chroma-red components each have the same sampling rate. The 4:4:4 notation may also be used to represent a red-green-blue (RGB) color format. As a further example, a very wide color space may be used, such as the color space defined by the International Commission on Illumination (CIE) 1931 XYZ. Video data represented with a high degree of accuracy may be mathematically almost lossless. However, high-precision representations may include redundancy and may not be optimal for compression. Therefore, a low-precision format is often used, which aims to display the color volume visible to the human eye.

Fig. 4 includes a diagram illustrating an example of a process 400 for converting high precision linear RGB 402 video data for the purpose of encoding the video data. The converted HDR data may have lower precision and may be more easily compressed. The example process 400 includes a non-linear conversion function 404 that may compress dynamic range, a color transition 406 that may produce a more compact or robust color space, and a quantization 408 function that may convert a floating point representation to an integer representation. The output of the quantization 408 function may be input into an encoder 410, which encoder 410 may compress or encode the data to produce an encoded bitstream. The encoder 410 may use, for example, the AVC HEVC or VP8/VP9/VP10 standard. The bit stream may be stored and/or transmitted.

In various examples, linear RGB 402 data, which may have a high dynamic range and floating point representation, may be compressed using a non-linear transfer function 404. An example of the nonlinear conversion function 404 is the perceptual quantizer defined in ST 2084. The output of the conversion function 404 may be transformed into a target color space by a color transition 406. The target color space may be a more suitable color space for compression, such as YCbCr. Quantization 408 may then be used to convert the data into an integer representation. The output of the quantization 408 may be provided to an encoder 410, which encoder 410 may generate an encoded bitstream from the data.

Fig. 5 includes a diagram illustrating an example of a process 500 for recovering converted HDR video data obtained from a decoded bitstream produced by decoder 522. The uncompressed or decoded video signal may be transmitted to the end consumer device using, for example, a high-speed digital interface. Examples of consumer electronics devices and transmission media include digital televisions, digital cable, satellite or terrestrial set top boxes, mobile devices, and related peripheral devices, such as Digital Versatile Disk (DVD) players and/or recorders, as well as other related decoding devices and consumer devices. In some examples, decoder 522 may perform the steps of process 500. In some examples, the end consumer electronic device may perform the steps of process 500.

Process 500 may operate on HDR video data converted according to process 400 of fig. 4 and may approximately produce high precision linear RGB 402 video data that is input into process 400. As shown in FIG. 5, the process 500 includes inverse quantization 524 (e.g., for converting an integer representation to a floating point representation), inverse color conversion 526, and inverse transfer function 528.

Inverse quantization 524 of fig. 5 comprises performing an inverse of the calculations performed for quantization 408 of fig. 4. Similarly, the inverse color transition 526 comprises the inverse of the calculations performed for the color transition 406, and the inverse transfer function 528 comprises the inverse of the calculations performed for the transfer function 402. For clarity, the following discussion provides examples of conversion functions 404, color transitions 406, and quantization 408, it being understood that these examples also apply to inverse conversion functions 528, inverse color transitions 426, and inverse quantization 524, unless otherwise provided. Additionally, the order of the steps of the example processes 400 and 500 illustrates the order in which the steps may be performed. In other examples, the steps may occur in a different order. For example, the color transition 406 may precede the transfer function 404. In another example, the inverse color transition 526 may be performed after the inverse transfer function 528. In other examples, additional processing may also occur. For example, spatial sub-sampling may be applied to the color components.

The conversion function may be used to map or map digital values in the image to or from optical energy. Optical energy, also referred to as optical power, is the degree to which a lens, mirror, or other optical system converges or diverges light. The transfer function may be applied to data in the image to compress the dynamic range. Compressing the dynamic range may enable video content to represent data with a limited number of bits. The conversion function may be a one-dimensional nonlinear function that may reflect the inverse of the electro-optical transfer function (EOTF) of the end consumer display (e.g., as specified for SDR in bt.709), or approximate the perception of luminance changes by the human visual system (e.g., as provided for HDR by the Perceptual Quantizer (PQ) conversion function specified in ST 2084). The electro-optical conversion function describes how to convert a digital value (referred to as a code level or code value) into visible light. For example, the EOTF may map the code level back to an illumination value. The inverse of the electro-optical transformation is the optical-electrical transform (OETF), which can generate code levels from illumination.

Fig. 6 includes a graph illustrating an example of an illuminance curve generated by a conversion function. Each curve plots luminance values at different code levels. Curves of the transfer function defined by bt.709 (curve 602) and ST2084 (curve 604), and a representative curve 606 of 10-bit SDR data are shown. Fig. 6 also shows the dynamic range achieved by each transfer function. In other examples, the curves may be plotted separately for red (R), green (G), and blue (B) color components.

ST2084 provides a conversion function that can more efficiently support higher dynamic range data. The conversion function of ST2084 is applied to the normalized linear R, G and B values, which results in non-linear representations, referred to herein as R ', G ', and B '. ST2084 also defines a normalization by NORM 10000, which correlates to a peak luminance of 10000 nits. The R ', G ', and B ' values can be calculated as follows:

R’＝PQ_TF(max(0,min(R/NORM,1)))

G’ ＝ PQ_TF(max(0, min(G/NORM,1)) ) (1)

B’＝PQ_TF(max(0,min(B/NORM,1)))

in equation (1), the conversion function PQ _ TF is defined as follows:

fig. 7 includes a graph illustrating an example of input values (e.g., linear color values) and corresponding output values (e.g., non-linear color values) to PQ _ TF normalized to a range of 0 to 1. As shown in the graph, 1% of the dynamic range of the input signal (e.g., representing low light levels) is converted to 50% of the dynamic range of the output signal.

The electro-optic transfer function may be defined as a function with floating point accuracy. By having floating point accuracy, when applying an inverse function (e.g., a photoelectric conversion function), the introduction of errors into the signal containing the non-linearity of the function can be avoided. The inverse conversion function specified by ST 2048 is as follows:

in equation (2), the inverse transfer function invertseppq _ TF is defined as follows:

with floating point accuracy, sequential application of EOTF and OETF can provide nearly accurate reconstruction without error. However, using EOTF to represent linear color data may not be optimal for streamlining or broadcast services. As described below, additional processing may produce a more compact representation of the non-linear R ' G ' B ' data with a fixed bit accuracy.

Other transfer functions and inverse transfer functions have been defined. The video coding system may use one of these other conversion functions and inverse conversion functions in place of or in addition to the conversion function provided by ST 2084.

The color transition may reduce the size of the color space of the linear RGB input. Image capture systems typically capture images as RGB data. However, the RGB color space may have a high degree of redundancy between color components. Thus, RGB is not optimal for producing a compact representation of the data. To achieve a more compact and robust representation, the RGB components may be converted to a less relevant color space, such as YCbCr, which is more suitable for compression. The YCbCr color space separates luminance in the form of luminance and color information in different uncorrelated components, including luminance (Y), chrominance-blue (Cb), and chrominance-red (Cr).

The YCbCr color space is one target color space used by bt.709. Bt.709 provides the following non-linear R ', G', and B 'values to non-constant luminance representations Y', Cb, and Cr transitions:

the transition provided by equation (3) may also be implemented using the following approximate transition, which may avoid the partitioning of the Cb and Cr components:

bt.2020 specifies the following transitions from R ', G ' and B ' to Y, Cb and Cr:

the transition provided by equation (5) may also be implemented using the following approximate transition, which may avoid the partitioning of the Cb and Cr components:

in these and other examples, the input color space (e.g., R 'G' B 'color space) and the output color space (e.g., Y' CBCr color space) remain normalized. Thus, for input values normalized in the range of 0 to 1, the output values will also be mapped to the range of 0 to 1. In some examples, the values of Cb and Cr are normalized to be in the range of-0.5 to 0.5, where both Cb and Cr values equal to 0 indicate gray. Color transformations performed with floating point accuracy can approach perfect reconstruction, resulting in lossless processing.

After the color transition, the input data now in the target color space may still be represented with a high bit depth (e.g., with floating point accuracy) and may be lossless. However, this degree of accuracy can be redundant and excessive for most consumer electronics applications. In some examples, 10-bit to 12-bit accuracy, in combination with the PQ transfer function, may be sufficient to have HDR data with 16 aperture steps with distortion just below what is noticeable by human vision. Most video coding systems can further encode HDR data with 10 bit accuracy.

Quantization may transform the data to a target bit depth. Quantization is a lossy process, meaning that some information is lost, and may be a source of inaccuracy in the output HDR data.

The following equations provide examples of quantization that may be applied to codewords in a target color space. In this example, the input values of Y, Cb and Cr with floating point accuracy may be translated into fixed bit depth values, BitDepthY for the Y value and BitDepthC for the chroma values (Cb and Cr).

In the above formula:

Round(x)＝Sign(x)*Floor(Abs(x)+0.5)

sign (x) ═ -1 (if x <0), 0 (if x ═ 0), 1 (if x >0)

Floor (x) maximum integer less than or equal to x

Abs (x) ═ x (if x > ═ 0), -x (if x <0)

Clip1Y(x)＝Clip3(0,(1<<BitDepthY)-1,x)

Clip1C(x)＝Clip3(0,(1<<BitDepthC)-1,x)

Clip3(x, y, z) ═ x (if z < x), y (if z > y), otherwise z.

In some cases, converting video data with a large color volume to video data with a more compact color volume may result in a dynamic range change. These dynamic range changes may be visible as distortions in the reconstructed video, such as color mismatch or bleeding. Dynamic Range Adjustment (DRA) is a technique for compensating for dynamic range changes and reducing possible distortions. DRA the following documents, which are hereby incorporated by reference in their entirety for all purposes: "Dynamic Range Adjustment SEI to enable High Dynamic Range video coding with Back-Compatible Capability," D.Rusanovskyy, A.K.Ramasubramonian, D.Bugdayci, S.Lee, J.Sole, and M.Karczewicz, VCEG document COM 16-C1027-E, Sep.2015.

In various examples, the DRA may be implemented using a piecewise linear function f (x) defined for a set of non-overlapping dynamic range partitions, also referred to herein as ranges, where each range partition or range includes a set of input values x (e.g., input color values). Ranges are denoted herein by { Ri }, where i is the index of each respective range, and i-0 … N-1, including 0 and N-1, where N is the total number of ranges used to define the DRA function. As an example, it may be assumed that the ranges are defined by the most significant and maximum x values belonging to each respective range Ri; for example for the input value x _i ,x _i+1 -1]，x _i And x _i+1 The minimum values of the ranges Ri and R (i +1) may be represented, respectively. Applied to the Y color component (e.g. luminance value) of the video, the DRA function S _y The scaling value S may be used _y,i And offset value O _y,i Is applied to each input value (that is, for each x e x _i ,x _i+1 -1]). Thus, a DRA function may be defined as a set of scaling and offset values for each input value, or S _y ＝{S _y,i ,O _y,i }。

Using this definition of the DRA function, for any range Ri and for each x ∈ [ x ] _i ,x _i+1 -1]The output value X may be calculated as follows:

X＝S _y,i ×(x-O _y,i ) (8)

the inverse DRA mapping for the luminance component Y may be done at the decoder. In this case, the DRA function S _y Can be scaled by a value S _y,i And offset value O _y,i Is defined by the inverse of (c). Inverse scaling values and offset values may be applied to each X ∈ [ X ] _i ,X _i+1 -1]。

Using this definition of the inverse DRA function, X ∈ [ X ] for any range Ri and for each output value _i ,X _i+1 -1]The reconstructed x value may be calculated as follows:

x＝X/S _y,i +O _y,i (9)

DRA mapping procedures may also be defined for the chroma components Cb and Cr (e.g., for encoding purposes). In the following example, u denotes a sampling point of a Cb color component belonging to the range Ri. In this example, u ∈ [ u ] _i ,u _i+1 -1]. DRA function S of chrominance samples _u The scaling value S may also be used _u,i And offset value to define O _u,i So that S _u ＝{S _u,i ,O _u,i }. Thus, the output value U can be calculated as follows:

U＝S _u,i ×(u-O _y,i )+Offset (10)

in equation (10), Offset is equal to 2 ^(bitdepth-1) And represents the bipolar Cb, Cr signal offset.

Inverse DRA mapping for the chroma components Cb and Cr may also be defined and may be performed at the decoder. In the following example, U represents a sampling of the remapped Cb color components from the range Ri, where U ∈ [ U ] U _i ,U _i+1 -1]. In this example, the Cb component may be reconstructed by the following equation:

u＝(U-Offset)/S _u,i +O _y,i (11)

in equation (11), Offset is equal to 2 ^(bitdepth-1) And represents the bipolar Cb, Cr signal excursion.

An additional technique for reducing distortion that may occur when modifying the color space of video is Luma-driven Chroma Scaling (LCS). Luminance-driven chroma scaling is proposed in the following documents, which are incorporated by reference in their entirety and for all purposes: JCTVC-W0101 HDR CE2 Report on CE2.a-1LCS, A.K.Ramasubramonian, J.Sole, D.Rusanovsky, D.Bugdayci, and M.Karczewicz.

LCS is a technique for adjusting chrominance information (e.g., Cb and Cr samples) by using luminance information associated with processed chrominance samples. Similar to the DRA method described above, the LCS method includes applying a scaling factor S to the Cb component _u And applying a scaling factor S to the Cr component _v,i . However, in the case of LCS, the DRA function is not defined as a piecewise linear function (e.g., for colors as in equations (3) or (4))Set of ranges accessible by the value u or v R _i Is defined as S _u ＝{S _u,i ,O _u, i }) and the LCS method uses the luminance value Y to derive a scaling factor for the chroma samples. For example, mapping chrominance samples u (or v) for the purpose of encoding video data may be performed using the following equation:

U＝S _u,i (Y)×(u-Offset)+Offset (12)

for decoding purposes, the reverse LCS procedure may be defined as follows:

u＝(U-Offset)/S _u,i (Y)+Offset (13)

as another example, for a given pixel located at (x, Y), the corresponding LCS function S is accessed from the use luminance value Y' (x, Y) _Cb (or S) _Cr ) The derived factors scale the chroma samples Cb (x, y) and/or Cr (x, y).

In the forward mapping process for chroma samples (e.g., when processing through encoding), the Cb (or Cr) values and associated luma values Y' are treated as a scaling function S to chroma _Cb (or S) _Cr ) And Cb or Cr is converted into Cb 'and Cr', as shown in the following equation (14).

Cb′(x,y)＝S _Cb (Y′(x,y))×Cb(x,y),

Cr′(x,y)＝S _Cr (Y′(x,y))×Cr(x,y) (14)

At the time of decoding, the inverse LCS procedure is applied, and the reconstructed Cb 'or Cr' is converted into Cb or Cr as shown in the following equation (15).

Fig. 8 includes a graph illustrating an example of an LCS function. In the present example, the chrominance components of the pixels having smaller luminance values are multiplied by smaller scaling factors.

To adjust the compression ratio at the encoder, embodiments including a block transform-based video coding scheme may utilize a scalar quantizer (such as described with respect to quantization unit 54 of fig. 13 and inverse quantization unit 86 of fig. 14) applied to the block transform coefficients:

Xq＝X/scalerQP

wherein Xq is a quantized code value of the transform coefficient X generated by applying a scalar scalerQP derived from the QP parameter; in most codecs, the quantized code values will be approximated as integer values (e.g., by rounding). In some embodiments, the quantization may be a different function that depends not only on the QP, but also on other parameters of the codec.

In some embodiments, a scalar value scalerQP is controlled using a Quantization Parameter (QP), where the relationship between QP and scalar quantizer is defined as follows, where k is a known constant:

scalerQP＝k*2^(QP/6) (16)

the inverse function defines the relationship between the scalar quantizer applied to the transform coefficients and the QP of HEVC (for example) as follows:

QP＝ln(scalerQP/k)*6/ln(2)； (17)

an additive change in QP value (e.g., deltaQP) will result in a multiplicative change in scalerQP value applied to the transform coefficients, respectively.

The DRA effectively applies a value, such as a scaledr value, to the pixel-like point values, and considering the transform properties, scalerQP values may be combined as follows:

Xq＝T(scaleDRA*x)/scaleQP

where Xq is the quantized transform coefficient resulting from the scaled transform T of x sample values and scaled with scaleQP applied in the transform domain. Thus, applying the multiplier scaleDRA in the pixel domain results in an effective change of the scalar quantizer scaledrp applied in the transform domain. This in turn can be interpreted as an additive change in QP parameters applied to the current processed data block:

dQP＝log2(scaleDRA)*6 (18)

where dQP is the approximate QP offset that HEVC introduces by deploying DRA on the input data.

Some of the most advanced video coding designs (such as HEVC) and newer designs being developed (such as VVC) may be effectively applied to process the current coding block Cb, taking advantage of a predefined correlation between luma and chroma QP values. This correlation can be used to achieve an optimal bit rate allocation between the luminance and chrominance components. An example of this correlation is represented by tables 8-10 of the HEVC specification, where QP values applied to decoding of chroma samples are derived from QP values used to decode luma samples. The relevant sections in which the chroma QP value is derived based on the QP value of the corresponding luma sample (the QP value applied to the block/TU to which the corresponding luma sample belongs), the chroma QP offset, and tables 8-10 of the HEVC specification are reproduced as follows:

when ChromaArrayType is not equal to 0, the following applies:

the variable qP _Cb And qP _Cr The derivation is as follows:

-if tu _ residual _ act _ flag [ xTbY ] [ yTbY ] is equal to 0, the following applies:

qPi _Cb ＝Clip3(-QpBdOffset _C ，57，Qp _Y +pps_cb_qp_offset+slice_cb_qp_offset+CuQpOffset _Cb ) (8-287)

qPi _Cr ＝Clip3(-QpBdOffset _C ，57，Qp _Y +pps_cr_qp_offset+slice_cr_qp_offset+CuQpOffset _Cr ) (8-288)

-otherwise (tu _ residual _ act _ flag [ xTbY ] [ yTbY ] equals 1), the following applies:

qPiCb＝Clip3(-QpBdOffsetC，57，QpY+PpsActQpOffsetCb+slice_act_cb_qp_offset+CuQpOffsetCb) (8-289)

qPi _Cr ＝Clip3(-QpBdOffsetC，57，QpY+PpsActQpOffsetCb+slice_act_cr_qp_offset+CuQpOffsetCr) (8-290)

-variable qP if ChromaArrayType equals 1 _Cb And qP _Cr Are respectively based on being equal to qPi _Cb And qPi _Cr Is set equal to Qp as specified in tables 8-10 _C The value of (c).

Else, then the variable qP _Cb And qP _Cr Are respectively based on being equal to qPi _Cb And qPi _Cr Is set equal to Min (qPi, 51).

Chrominance quantization parameter Qp 'of Cb and Cr components' _Cb And Qp' _Cr The derivation is as follows:

Qp′ _Cb ＝qP _Cb +QpBdOffset _C (8-291)

Qp′ _Cr ＝qP _Cr +QpBdOffset _C (8-292)

HEVC tables 8-10 Qp as a function of qPi for ChromaArrayType equal to 1 _C Norm of

qPi	＜30	30	31	32	33	34	35	36	37	38	39	40	41	42	43	＞43
																	Qp C	＝qPi	29	30	31	32	33	33	34	34	35	35	36	36	37	37	＝qPi-6

In a video coding system employing uniform scalar quantization in the transform domain and pixel domain scaling with DRA, the derivation of the scaled DRA values applied to the chroma samples (Sx) may depend on:

-S _Y : luminance scaling values for associated luminance samples

-S _CX : scaling derived from the color gamut of content, where CX represents Cb or Cr as applicable

-S _corr : correction scaling term based on accounting for mismatches in transform coding and DRA scaling, e.g. for compensating for the dependencies introduced by tables 8-10 of HEVC

-S _X ＝fun(S _Y ，S _CX ，S _corr )。

One example includes defining separable functions as follows: s _X ＝f1(S _Y )*f2(S _CX )*f3(S _corrr )。

Embodiments include HDR video encoding systems that employ uniform scalar quantization in the transform domain and pixel domain scaling with DRA. The derivation of the chroma DRA scaling Sx depends on the following: luminance DRA scaling value S _Y Chroma scaling (S) associated with a color container and a natural color gamut of content being encoded _CX ) And parameters for the correlation between the QP settings (also known as the base QP) of the hybrid video codec used to compress the content and the luma and chroma QP settings employed by the codec. Container scaling factor (S) _CX ) The term can be derived from the QP offset value corresponding to the basic QP according to equation (16), as suggested by the following document in ITU-T h.sup15 (chroma QP offset configuration): conversion and coding tasks for HDR// WCG Y' CbCr 4:2:0video with PQ transfer characteristics, Recommendation H.Sup15(01/17),https://www.itu.int/rec/T-REC-H.Sup15-201701-I/ en。

for embodiments of DRA video coding systems based on HEVC, VVC, or similar standards, there may also be a chroma scaling correction term (S) _corr ) (which illustrates chroma QP corrections introduced by the chroma QP table utilized by the decoder) similar to that defined in tables 8-10 of HEVC.

Fig. 9 includes a graph plotting y-values for a range of x-values (curve 910), showing a comparison of an example of chroma QP offset (curve 910) as a function of input QP and a linear approximation of the correlation (curve 920)

Fig. 10 includes a graph plotting y values for a range of values for x, showing a comparison of chroma QP correction (curve 1010) and its linear approximation (curve 1020) using HEVC tables 8-10.

The latter two terms, Scx and Scorr, are derived from the integer QP settings of the codec; the final scaling function derived from equation 16 is therefore characterized by a discontinuity (staircase-like function) resulting from the integer value QP, see dashed lines 910 and 1010 in fig. 9 and 10. These discontinuities may affect the performance of encoding using DRAs, resulting in severe visual artifacts and quality degradation. Therefore, it may be desirable to use DRA functions that avoid such discontinuities.

Embodiments include improving aspects of video coding with dynamic range adaptation, including efficient signaling mechanisms. It should be understood that one or more of these aspects may be used independently or in conjunction with other methods.

One embodiment includes an encoding system that includes a first parametric functional relationship defining a chroma DRA scaling and encoding parameters, such as QP settings used by a block transform-based hybrid video codec for encoding content, or similar parameters that specify the rate/quality of the codec, such that the function may be linear or non-linear (not necessarily piecewise linear) without discontinuities. In some embodiments, a parameter function may be defined for each picture of a sequence, either explicitly or using a predetermined method, based on the position of the picture in the GOP/intra period/random access period/sequence.

Alternatively, embodiments may include signaling (by the video encoder 104 in the encoded video bitstream) the first parameter function in the encoded bitstream to the decoder by signaling the associated parameter in the bitstream. In such embodiments, the decoder uses these decoded parameters to derive a parameter function, and uses this function to derive chroma scaling values to be applied during the DRA. In some embodiments, the parametric function may be implemented as a parameterized one-dimensional (1D) function. In some alternative embodiments, the first parametric function may be derived using an algorithm at the decoder, and therefore does not result in any signaling (i.e., no explicit signaling of the first parametric function).

In some embodiments, the encoding system may include defining a second parametric function to specify (or for deriving) the chroma DRA scaling correction term as a function of one or more parameters associated with the codec, and using the second function to derive the chroma scaling correction term. In some embodiments, the chroma DRA scaling correction term is defined as a function of the QP associated with the luma and the offset associated with the luma and chroma.

Alternatively, embodiments may include signaling the second parameter function to the decoder (by the video encoder 104 in the encoded video bitstream) using the parameter; deriving a second parametric function at the decoder; a chroma scaling correction term is derived at the decoder using the derived function.

In some alternatives, the second parametric function may be a piecewise linear function. In some alternatives, the second parametric function may be specified as a parameterized one-dimensional function, and the parameters may be signaled to the decoder 112.

In other alternatives, the second parametric function may be predetermined for use at the encoder and the decoder. In such embodiments, a fixed second function may be used, or one function of a prescribed set of functions may be identified by parameters that are implicitly or explicitly signaled.

In some embodiments, the definition of the first parametric function may use fixed point arithmetic. Optionally, the derivation of the first parametric function may also be done using fixed point arithmetic.

In some embodiments, the definition of the second parametric function may use fixed point arithmetic. Alternatively, the derivation of the second parametric function may also be done using fixed point arithmetic.

Further details of examples of how one or more systems and methods in accordance with the various aspects described above may be implemented are now described.

In some embodiments, the real-valued chroma DRA scaling value may be defined directly as a function, without intermediate representation by an integer QP value. Scaling S _CX The parameter k may be used _X A and b are defined as follows:

S _CX ＝f1(k _X *(a*QP+b))

where f1() describes the relationship between a real-valued QP term (e.g., QP offset value) and a DRA scaling value (e.g., scaled logarithmic derivative from QP parameters, as shown in equation 16).

The parameters a and b represent the scaling and offset terms, and k _X Is a component specific scaling term that may be different for Cb and Cr. Clipping functions may also be used in the definition of the scaling function in order to limit the maximum and minimum contributions due to the container. For example:

S _CX ＝Clip3(s _max ,s _min ,k _X *(a*QP+b))

wherein s is _max And s _min Are the maximum and minimum scaling values to which the function is clipped. It will be appreciated that the above-described function is merely an example of a scaling term that is a function of QP, which may be defined based on additional parameters (e.g., chroma offset, associated luma sample value, chroma sample value, etc.) using additional parameters.

Parameter k _x 、a、b、s _max And s _min The fixed/variable length code may be used for signaling in the bitstream. The number of bits associated with the signaling of one or more of these parameters may also be signaled in the bitstream.

In some alternative embodiments, the QP for the scaling derivation mechanism may be integrated in a defined function as follows, and the parameters of the function f2() may be signaled. Alternatively, the function f2() is known at the encoder 104 and the decoder 112 as side information (fixed in the codec or otherwise predefined independently of the coding layer of the bitstream) and does not require signaling.

S _CX ＝f2(QP)

Scaling the correction term S _corr The derivation may be based on basic QP as follows. Assume sQP is a parameterized function sQP (QP) defined based on the basic QP:

localQP1＝sQP(QP)

the sQP value may also be defined based on other variables, such as chroma QP offset and luma delta QP value. In other alternatives, the sQP value may additionally be dependent on the luminance DRA scaling S _Y . The scaling correction term may be determined by the difference of two local QP valuesObtained as follows:

qpDiff＝sQP(QP+chromaQPOffset)–sQP(QP+chromaQPOffset+deltapQP)

S _corr ＝k*2^(qpDiff/6)

where deltaQP represents an additive QP change applied to the current pixel or block of pixels. Such QP changes can be introduced at the block transform domain or by pixel domain scaling with Sy. In the latter case, the deltaQP variable may be derived as shown in equation 17:

deltaQP＝(ln(S _Y /k)*6/ln(2))

note that dependence on chromaQPOffset and S _Y How they are defined, the above equations may be different to account for the negative sign or inverse.

In some embodiments, similar to tables 8-10 of HEVC, the correlation of chroma QP to luma QP may not be defined using a list integer value QP LUT; instead, a function that allows real-valued mapping may be used as follows:

QP _corr ＝fun(QP _est )

QP _est ＝Clip3(-QpBdOffsetC,57,QpY _est +PpsActQpOffsetCb+

slice _ act _ cb _ QP _ offset + CuQpOffsetCb) (8-289) where QP _corr Is derived from a real-valued variable QpY _est A derived corrected real-valued variable, which may be estimated from the luminance scaling applied to the corresponding Y samples.

In such embodiments, the chroma QP values utilized in the decoder derivation may be determined by dividing the QP into a plurality of values _corr The value is rounded to an integer value to produce, and the chroma scales the correction value S _corr Can be directly derived from the real QP _corr And (4) generating.

In some embodiments, the correlation of chroma QP offsets or their corresponding chroma scaling representations reflecting the color container/gamut representation may be defined at the decoder side as a QP dependent function or as a tabulated LUT from integer QP values.

Fig. 11 includes a flow diagram illustrating an example of a process 1100 for encoding video data. Process 1100 may be implemented, for example, by an encoding device including a memory and a processor. In this example, the memory may be configured to store video data and the processor may be configured to perform the steps of process 1100 of fig. 11. For example, the encoding device may include a non-transitory computer-readable medium capable of storing instructions that, when executed by a processor, enable the processor to perform the steps of process 1100. In some examples, the encoding device 104 may include a camera as the video source 102 for capturing video data.

At block 1102, method 1100 includes obtaining video data at video encoding device 104 to obtain a portion of a video picture of the video data. The video data includes parameters describing an uninterrupted function for dynamic range adjustment of colors in a portion of a video picture. The video data may be obtained by the encoding device 104 from the video source 102, including by capturing from a camera or from storage for encoding or re-encoding.

Next, at block 1104, video encoding device 104 generates a syntax structure indicating parameters of the DRA function. Moving to block 1110, the encoding device 104 generates encoded video data from the video data. The syntax structure is included within the encoded video data.

Fig. 12 includes a flow diagram illustrating an example of a process 1200 for decoding video data. Process 1200 may be implemented, for example, by decoding device 112 comprising a memory and a processor. In this example, the memory may be configured to store encoded video data and the processor may be configured to perform the steps of process 1200 of fig. 12. For example, the decoding device 112 may include a non-transitory computer-readable medium capable of storing instructions that, when executed by a processor, enable the processor to perform the steps of the process 1200. In some examples, decoding device 112 may include a camera for capturing video data. In some examples, decoding device 112 may include a video destination device 122, such as a display for displaying decoded video data. In some examples, decoding device 112 is a mobile device having a camera for capturing video data and a display for displaying the video data.

At block 1102, the method 1200 includes obtaining video data at the video decoding device 112. The decoding device 112 may decode some or all of the video data from an encoded video bitstream, such as a video bitstream generated according to the method 1100. Some of the data may also be obtained from a storage device of the encoding apparatus 112.

Next, at block 1214, the decoding device 112 determines, for a portion of a video picture from the encoded video data, a syntax structure that includes parameters describing an uninterrupted function for dynamic range adjustment of colors in the portion of the video picture. The function may include an integer quantization parameter as an input. In one such embodiment, the function relates a value derived from an integer quantization parameter using a logarithmic function to a value associated with dynamic range adjustment of a portion of video data.

Moving to block 1214, the video decoding device 112 decodes a portion of a video picture based on data decoded from the video bitstream. At block 1216, video decoding device 112 applies the function to samples in a portion of the video picture to perform dynamic range adjustment.

The video encoding device 104 and the video decoding device 112 may operate according to a video coding standard, such as ITU-T h.265, also known as High Efficiency Video Coding (HEVC) or extensions thereof, such as multi-view and/or scalable video coding extensions. Alternatively, the video encoding device 104 and the video decoding device 112 may operate according to other proprietary or industry standards, such as joint exploration test model (JEM) or ITU-T H.266, also known as Universal video coding (VVC). The latest draft of the VVC standard is described in the following documents: "Versatile Video Coding (Draft 3)," Joint Video Experts Team (JVT) of ITU-T SG 16WP 3and ISO/IEC JTC 1/SC 29/WG 11,12 ^th Meeting: Macao, CN,3-12October 2018, JVOET-L1001-v 9 (hereinafter referred to as "VVC draft 3"). However, the techniques of this disclosure are not limited to any particular encoding standard. In particular, embodiments may include VVCs incorporating future versions of one or more embodiments disclosed herein.

In general, the video encoding device 104 and the video decoding device 112 may perform block-based picture coding. The term "block" generally refers to a structure that includes data to be processed (e.g., encoded, decoded, or used in an encoding and/or otherwise decoding process). For example, a block may comprise a two-dimensional matrix of samples of luminance and/or chrominance data. In general, the video encoding device 104 and the video decoding device 112 may encode video data represented in YUV (e.g., Y, Cb, Cr) format. That is, rather than encoding red, green, and blue (RGB) data for samples of a picture, the video encoding device 104 and the video decoding device 112 may encode luminance and chrominance components, where the chrominance components may include both red-tone chrominance components and blue-tone chrominance components. In some examples, the video encoding device 104 converts the received RGB format data into a YUV representation prior to encoding, and the video decoding device 112 converts the YUV representation into an RGB format. Alternatively, a pre-processing and post-processing unit (not shown) may perform these transitions.

The present disclosure may generally refer to encoding (e.g., encoding and decoding) of a picture to include a process of encoding or decoding data of the picture. Similarly, the present disclosure may refer to the encoding of a picture block to include processes of encoding or decoding data of the block, such as prediction and/or residual coding. The coded video bitstream typically includes a series of values representing coding decisions (e.g., coding modes) and syntax elements that partition the picture into blocks. Thus, a reference to encoding a picture or block is generally understood to be an encoded value of a syntax element forming the picture or block.

HEVC defines various blocks, including Coding Units (CUs), Prediction Units (PUs), and Transform Units (TUs). According to HEVC, a video encoder, such as video coding device 104, partitions a Coding Tree Unit (CTU) into CUs according to a quadtree structure. That is, the video encoder partitions the CTU and CU into four equal, non-overlapping squares, and each node of the quadtree has zero or four child nodes. A node without a child node may be referred to as a "leaf node," and a CU of such a leaf node may include one or more PUs and/or one or more TUs. The video encoder may further partition the PU and TU. For example, in HEVC, the Residual Quadtree (RQT) represents the partitioning of a TU. In HEVC, a PU represents inter prediction data and a TU represents residual data. The CU to be intra-predicted includes intra-prediction information, such as an intra-mode indication.

As another example, the video encoding device 104 and the video decoding device 112 may be configured to operate in accordance with JEM or VVC. According to JEM or VVC, a video encoder, such as video encoding device 104, partitions a picture into multiple Coding Tree Units (CTUs). The video encoding device 104 may partition the CTUs according to a tree structure, such as a binary Quadtree (QTBT) structure or a multi-type tree (MTT) structure. The QTBT structure removes the concept of multiple partition types, such as the separation between CU, PU and TU of HEVC. The QTBT structure comprises two levels: a first hierarchy partitioned according to a quadtree partition, and a second hierarchy partitioned according to a binary tree partition. The root node of the QTBT structure corresponds to the CTU. Leaf nodes of the binary tree correspond to Coding Units (CUs).

In the MTT split structure, a block may be split using Quadtree (QT) splitting, Binary Tree (BT) splitting, and one or more types of Ternary Tree (TT) splitting. A ternary tree partition is a partition that divides a block into three sub-blocks. In some examples, the ternary tree partitioning divides a block into three sub-blocks without centrally dividing the original block. The partition types (e.g., QT, BT, and TT) in MTT may be symmetric or asymmetric.

As described above, the source device may perform the encoding, and thus may include an encoding device to perform this function. Also as described above, the destination device may perform decoding and may therefore include a decoding device. Example details of the encoding device 104 and the decoding device 112 of fig. 1 are shown in fig. 13 and 14, respectively. Fig. 13 is a block diagram illustrating an example encoding device 104 that may implement one or more of the techniques described in this disclosure. The encoding device 104 may, for example, generate a syntax structure described herein (e.g., a syntax structure of a VPS, SPS, PPS, or other syntax element). The encoding device 104 may perform intra-prediction and inter-prediction encoding on video blocks within a video slice. As previously described, intra-coding relies at least in part on spatial prediction to reduce or remove spatial redundancy within a given video frame or picture. Inter-coding relies at least in part on temporal prediction to reduce or eliminate temporal redundancy in adjacent or surrounding frames of a video sequence. Intra mode (I-mode) may refer to any of several space-based compression modes. An inter mode, such as unidirectional prediction (P-mode) or bidirectional prediction (B-mode), may refer to any of several time-based compression modes.

The encoding device 104 includes a division unit 35, a prediction processing unit 41, a filter unit 63, a picture memory 64, an adder 50, a transform processing unit 52, a quantization unit 54, and an entropy encoding unit 56. The prediction processing unit 41 includes a motion estimation unit 42, a motion compensation unit 44, and an intra prediction processing unit 46. For video block reconstruction, encoding device 104 also includes inverse quantization unit 58, inverse transform processing unit 60, and adder 62. Filter unit 63 is intended to represent one or more loop filters such as deblocking filters, Adaptive Loop Filters (ALF) and Sample Adaptive Offset (SAO) filters. Although filter unit 63 is shown in fig. 13 as an in-loop filter, in other configurations, filter unit 63 may be implemented as a post-loop filter. Post-processing device 57 may perform additional processing on the encoded video data generated by encoding device 104. In some cases, the techniques of this disclosure may be implemented by the encoding device 104. However, in other cases, one or more techniques of the present disclosure may be implemented by post-processing device 57.

As shown in fig. 13, the encoding device 104 receives video data, and the division unit 35 divides the data into video blocks. The partitioning may also include partitioning into slices, slice segments, slices, or other larger units, as well as video block partitioning, e.g., according to a quadtree structure of LCUs and CUs. The encoding device 104 generally shows components that encode video blocks within a video slice to be encoded. A slice may be divided into a plurality of video blocks (and possibly into a set of video blocks called slices). The prediction processing unit 41 may select one of a plurality of possible encoding modes, such as an intra prediction encoding mode or an inter prediction encoding mode, for the current video block based on the error result (e.g., encoding rate, distortion level, and the like). The prediction processing unit 41 may provide the resulting intra or inter coded block to a first adder 50 to generate residual block data and to a second adder 62 to reconstruct the coded block for use as a reference picture.

Intra-prediction processing unit 46 within prediction processing unit 41 may perform intra-prediction encoding of the current video block relative to one or more neighboring blocks in the same frame or slice as the current block to be encoded to provide spatial compression. Motion estimation unit 42 and motion compensation unit 44 within prediction processing unit 41 perform inter-prediction encoding of the current video block relative to one or more prediction blocks in one or more reference pictures to provide temporal compression.

The motion estimation unit 42 may be configured to determine an inter prediction mode for a video slice from a predetermined mode of the video sequence. The predetermined pattern may specify video slices in the sequence as P slices, B slices, or Generalized P and B (GPB) slices (slices with the same reference picture lists (list 0 and list 1)). The motion estimation unit 42 and the motion compensation unit 44 may be highly integrated, but are shown separately for conceptual purposes. The motion estimation performed by motion estimation unit 42 is a process of generating motion vectors, which estimates the motion of video blocks. For example, a motion vector may indicate the displacement of a Prediction Unit (PU) of a video block within a current video frame or picture relative to a prediction block within a reference picture.

A prediction block is a block that is found to closely match a PU of a video block to be encoded in terms of pixel differences, which may be determined by the Sum of Absolute Differences (SAD), the Sum of Squared Differences (SSD), or other difference metrics. In some examples, encoding device 104 may calculate values for sub-integer pixel positions of reference pictures stored in picture memory 64. For example, the encoding device 104 may interpolate values for quarter pixel positions, eighth pixel positions, or other fractional pixel positions of the reference picture. Accordingly, the motion estimation unit 42 may perform a motion search with respect to the full pixel position and the partial pixel position and output a motion vector having fractional pixel accuracy.

Motion estimation unit 42 calculates a motion vector for a PU of a video block in an inter-coded slice by comparing the location of the PU to locations of prediction blocks of reference pictures. The reference picture may be selected from a first reference picture list (list 0) or a second reference picture list (list 1), each list identifying one or more reference pictures stored in picture memory 64. The motion estimation unit 42 sends the calculated motion vector to the entropy coding unit 56 and the motion compensation unit 44.

The motion compensation performed by the motion compensation unit 44 may include taking or generating a prediction block based on a motion vector determined by motion estimation, possibly performing an interpolation of sub-pixel precision. When receiving the motion vector for a PU of the current video block, motion compensation unit 44 may locate the prediction block to which the motion vector points in the reference picture list. Encoding device 104 forms a residual video block by subtracting pixel values of the prediction block from pixel values of the current video block being encoded, thereby forming pixel difference values. The pixel difference values form residual data for the block and may include luminance and chrominance difference components. Adder 50 represents one or more components that perform this subtraction operation. Motion compensation unit 44 may also generate syntax elements associated with the video blocks and the video slice for use by decoding device 112 in decoding the video blocks of the video slice.

As described above, the intra prediction processing unit 46 may intra predict the current block, as an alternative to the inter prediction performed by the motion estimation unit 42 and the motion compensation unit 44. In particular, the intra prediction processing unit 46 may determine an intra prediction mode for encoding the current block. In some examples, the intra-prediction processing unit 46 may encode the current block using various intra-prediction modes, e.g., during separate encoding processes, and the intra-prediction processing unit 46 may select an appropriate intra-prediction mode to use from the tested modes. For example, the intra prediction processing unit 46 may calculate a rate-distortion value using rate-distortion analysis for various tested intra prediction modes, and may select an intra prediction mode having the best rate-distortion characteristics among the tested modes. Rate-distortion analysis typically determines the amount of distortion (or error) between the encoded block and the original, unencoded block that was encoded to produce the encoded block, as well as the bit rate (i.e., the number of bits) used to produce the encoded block. The intra-prediction processing unit 46 may calculate a ratio from the distortion and rate of various encoded blocks to determine which intra-prediction mode exhibits the best rate-distortion value for the block.

In any case, after selecting the intra-prediction mode for a block, intra-prediction processing unit 46 may provide information to entropy encoding unit 56 indicating the intra-prediction mode selected for the block. Entropy encoding unit 56 may encode information indicating the selected intra-prediction mode. The encoding device 104 may include in the transmitted bitstream the configuration data definitions of the encoding contexts of the various blocks and an indication of the most probable intra prediction mode, intra prediction mode index table, and modified intra prediction mode index table for each context. The bitstream configuration data may include an intra prediction mode index table and a modified intra prediction mode index table (also referred to as a codeword mapping table).

After prediction processing unit 41 generates a prediction block for the current video block via inter prediction or intra prediction, encoding device 104 forms a residual video block by subtracting the prediction block from the current video block. The residual video data in the residual block may be included in one or more TUs and applied to the transform processing unit 52. The transform processing unit 52 transforms the residual video data into residual transform coefficients using a transform such as Discrete Cosine Transform (DCT) or a conceptually similar transform. Transform processing unit 52 may transform the residual video data from the pixel domain to a transform domain, such as the frequency domain.

The transform processing unit 52 may send the resulting transform coefficients to the quantization unit 54. The quantization unit 54 quantizes the transform coefficients to further reduce the bit rate. The quantization process may reduce the bit depth associated with some or all of the coefficients. The degree of quantization may be modified by adjusting the quantization parameter. In some examples, quantization unit 54 may then perform a scan of a matrix comprising quantized transform coefficients. Alternatively or additionally, the entropy encoding unit 56 may perform scanning.

After quantization, the entropy encoding unit 56 entropy encodes the quantized transform coefficients. For example, entropy encoding unit 56 may perform Context Adaptive Variable Length Coding (CAVLC), Context Adaptive Binary Arithmetic Coding (CABAC), syntax-based context-adaptive binary arithmetic coding (SBAC), probability interval entropy (PIPE) coding, or another entropy encoding technique. After entropy encoding by entropy encoding unit 56, the encoded bitstream may be transmitted to decoding device 112 or archived for later transmission or retrieval by decoding device 112. Entropy encoding unit 56 may also entropy encode the motion vectors and other syntax elements of the current video slice being encoded.

Inverse quantization unit 58 and inverse transform processing unit 60 apply inverse quantization and inverse transform, respectively, to reconstruct the residual block in the pixel domain for later use as a reference block for a reference picture. Motion compensation unit 44 may calculate the reference block by adding the residual block to a prediction block of one of the reference pictures within the reference picture list. Motion compensation unit 44 may also apply one or more interpolation filters to the reconstructed residual block to calculate sub-integer pixel values for use in motion estimation. Adder 62 adds the reconstructed residual block to the motion compensated prediction block produced by motion compensation unit 44 to produce a reference block for storage in picture memory 64. The reference block may be used by motion estimation unit 42 and motion compensation unit 44 as a reference block for inter-predicting blocks in subsequent video frames or pictures.

In this manner, the encoding device 104 of fig. 13 represents an example of a video encoder configured to generate a syntax of an encoded video bitstream. As described above, the encoding device 104 may, for example, generate a data structure that includes parameters of a piecewise linear function. Encoding device 104 may perform any of the techniques described herein, including the processes described above with reference to fig. 11 and 12. The techniques of this disclosure have generally been described with respect to encoding device 104, but as noted above, some of the techniques of this disclosure may also be implemented by post-processing device 57. Further, devices having similar or different components may be used to perform the techniques described herein in addition to the example encoding device 104.

Fig. 14 is a block diagram illustrating an example decoding device 112. The decoding apparatus 112 includes an entropy decoding unit 80, a prediction processing unit 81, an inverse quantization unit 86, an inverse transform processing unit 88, an adder 90, a filter unit 91, and a picture memory 92. The prediction processing unit 81 includes a motion compensation unit 82 and an intra prediction processing unit 84. In some examples, the decoding device 112 may perform a decoding process that is generally the reverse of the encoding process described for the encoding device 104 from fig. 13.

During the decoding process, the decoding device 112 receives an encoded video bitstream that represents video blocks and associated syntax elements of the encoded video slice sent by the encoding device 104. In some examples, the decoding device 112 may receive an encoded video bitstream from the encoding device 104. In some examples, decoding device 112 may receive an encoded video bitstream from a network entity 79, such as a server, a media-aware network element (MANE), a video editor/splicer, or other such device configured to implement one or more of the techniques described above. Network entity 79 may or may not include encoding device 104. Some of the techniques described in this disclosure may be implemented by network entity 79 prior to network entity 79 transmitting the encoded video bitstream to decoding device 112. In some video decoding systems, network entity 79 and decoding device 112 may be part of separate devices, while in other cases, the functions described for network entity 79 may be performed by the same device that includes decoding device 112.

The entropy decoding unit 80 of the decoding apparatus 112 entropy decodes the bitstream to generate quantized coefficients, motion vectors, and other syntax elements. The entropy decoding unit 80 forwards the motion vectors and other syntax elements to the prediction processing unit 81. The decoding device 112 may receive the syntax elements at the video slice level and/or the video block level. Entropy decoding unit 80 may process and parse fixed-length syntax elements and variable-length syntax elements in one or more parameter sets, such as VPS, SPS, and PPS.

When a video slice is encoded as an intra-coded (I) slice, the intra-prediction processing unit 84 of the prediction processing unit 81 may generate prediction data of a video block of the current video slice based on the signaled intra-prediction mode and data from a previously decoded block of the current frame or picture. When a video frame is encoded as an inter-coded (i.e., B, P or GPB) slice, motion compensation unit 82 of prediction processing unit 81 generates a prediction block for a video block of the current video slice based on the motion vector and other syntax elements received from entropy decoding unit 80. The prediction block may be generated from one of the reference pictures within the reference picture list. Decoding device 112 may construct reference frame lists, list 0 and list 1, using default construction techniques based on reference pictures stored in picture memory 92.

Motion compensation unit 82 determines prediction information for video blocks of the current video slice by parsing the motion vectors and other syntax elements and uses the prediction information to generate a prediction block for the current video block being decoded. For example, motion compensation unit 82 may use one or more syntax elements in the parameter set to determine a prediction mode (e.g., intra or inter prediction) for encoding video blocks of the video slice, an inter prediction slice type (e.g., B-slice, P-slice, or GPB-slice), construction information for one or more reference picture lists of the slice, a motion vector for each inter-coded video block of the slice, an inter prediction state for each inter-coded video block of the slice, and other information for decoding video blocks in the current video slice.

The motion compensation unit 82 may also perform interpolation based on an interpolation filter. The motion compensation unit 82 may use an interpolation filter used by the encoding device 104 during encoding of the video block to calculate an interpolation of sub-integer pixels of the reference block. In this case, the motion compensation unit 82 may determine an interpolation filter used by the encoding device 104 according to the received syntax element, and may generate the prediction block using the interpolation filter.

The inverse quantization unit 86 inversely quantizes or dequantizes the quantized transform coefficient provided in the bitstream and decoded by the entropy decoding unit 80. The inverse quantization process may include using a quantization parameter calculated by the encoding device 104 for each video block in the video slice to determine a degree of quantization and, likewise, a degree of inverse quantization that should be applied. Inverse transform processing unit 88 applies an inverse transform (e.g., an inverse DCT or other suitable inverse transform), an inverse integer transform, or a conceptually similar inverse transform process to the transform coefficients in order to generate a residual block in the pixel domain.

After motion compensation unit 82 generates a prediction block for the current video block based on the motion vector and other syntax elements, decoding device 112 forms a decoded video block by adding the residual block from inverse transform processing unit 88 to the corresponding prediction block generated by motion compensation unit 82. Adder 90 represents one or more components that perform the summation operation. If desired, a loop filter (in or after the encoding loop) may also be used to smooth pixel transitions or otherwise improve video quality. The filter unit 91 is intended to represent one or more loop filters, such as deblocking filters, Adaptive Loop Filters (ALF) and Sample Adaptive Offset (SAO) filters. Although the filter unit 91 is shown in fig. 14 as an in-loop filter, in other configurations the filter unit 91 may be implemented as a post-loop filter. The decoded video blocks in a given frame or picture are then stored in picture memory 92, which picture memory 92 stores reference pictures for subsequent motion compensation. Picture memory 92 also stores decoded video for later presentation on a display device, such as video destination device 122 shown in fig. 1.

The decoding device 112 of fig. 14 represents an example of a video decoder configured to parse the syntax of an encoded video bitstream and approximately reproduce the original video data for subsequent display. As described above, the decoding device may, for example, parse a data structure including parameters of a piecewise linear function and apply the piecewise linear function to the decoded data to perform dynamic range adjustment. Decoding device 112 may perform any of the techniques discussed herein, including the processes described above with reference to fig. 11 and 12. Additionally, devices other than the example decoding device 112 having similar or different components may be used to perform the techniques described herein. In some embodiments, the DRA is performed after the picture is stored in picture memory 64 of fig. 13 or picture memory 92 of fig. 14. In other embodiments, the picture samples to which DRA adjustment is applied are placed in picture store 64 of fig. 13 or picture store 92 of fig. 14.

Certain aspects and embodiments of the disclosure are disclosed above. It should be recognized that some of these aspects and embodiments may be applied independently, and some of them may be applied in combination, as will be apparent to those skilled in the art. In the following description, for purposes of explanation, specific details are set forth in order to provide a thorough understanding of the embodiments of the application. It may be evident, however, that the various embodiments may be practiced without these specific details. The drawings and description are not to be taken in a limiting sense. In particular, this description provides examples only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the description of the examples will provide those skilled in the art with an enabling description for implementing the examples. It being understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the application as set forth in the appended claims.

In the above description, specific details are given to provide a thorough understanding of the embodiments. However, it will be understood by those of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown in block diagram form as components in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments.

Furthermore, it is noted that the various embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be rearranged. A process is terminated when its operations are completed, but could have additional steps not included in the figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a procedure corresponds to a function, its termination may correspond to a return of the function to the calling function or the main function.

The term "computer-readable medium" includes, but is not limited to portable or non-portable storage devices, optical storage devices, and various other media capable of storing, containing, or carrying instruction(s) and/or data. Computer-readable media may include non-transitory media in which data may be stored and which do not include carrier waves and/or transitory electronic signals that propagate wirelessly or through a wired connection. Examples of non-transitory media may include, but are not limited to, magnetic disks or tapes, optical storage media such as Compact Disks (CDs) or Digital Versatile Disks (DVDs), flash memory, or memory devices. A computer-readable medium may have stored thereon code and/or machine-executable instructions that may represent procedures, functions, subroutines, programs, routines, subroutines, modules, software packages, classes, or any combination of instructions, data structures, or program statements. A code segment may be coupled to another code segment or a hardware circuit by passing and/or receiving information, data, arguments, parameters, or memory contents. Information, arguments, parameters, data, etc. may be passed, forwarded, or transmitted via any suitable means including memory sharing, message passing, token passing, network transmission, etc.

Furthermore, embodiments may be implemented by hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware or microcode, the program code or code segments (e.g., a computer program product) to perform the necessary tasks may be stored in a computer-readable or machine-readable medium. The processor(s) may perform the necessary tasks.

The need for efficient video coding techniques becomes more important as more and more devices and systems provide consumers with the ability to consume digital video data. Video coding is required to reduce the storage and transmission requirements needed to process the large amounts of data present in digital video data. Various video encoding techniques may be used to compress video data into a form that uses a lower bit rate while maintaining high video quality. As used herein, "coding" may refer to "encoding" and "decoding", particularly when the encoding and decoding processes operate in a similar manner (e.g., both encoding and decoding may include applying a transform, with the encoding process applying the transform and the decoding process applying the inverse transform).

In the foregoing description, aspects of the present application have been described with reference to specific embodiments thereof, but those skilled in the art will recognize that the present application is not limited thereto. Thus, although illustrative embodiments of the present application have been described in detail herein, it is to be understood that the inventive concepts may be otherwise variously embodied and employed, and that the appended claims are intended to be construed to include such variations unless limited by the prior art. Various features and aspects of the above-described examples may be used alone or in combination. Moreover, embodiments may be utilized in any number of environments and applications beyond those described herein without departing from the broader spirit and scope of the specification. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense. For purposes of illustration, the methods are described in a particular order. It should be understood that in other embodiments, the methods may be performed in an order different than that described.

Where a component is described as being "configured to" perform certain operations, such configuration may be achieved, for example, by designing electronic circuitry or other hardware to perform the operations, by programming programmable electronic circuitry (e.g., a microprocessor or other suitable electronic circuitry) to perform the operations, or by any combination thereof.

The various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, firmware, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

The techniques described herein may also be implemented in electronic hardware, computer software, firmware, or any combination thereof. Such techniques may be implemented in any of a variety of devices, such as general purpose computers, wireless communication device handsets, or integrated circuit devices having multiple uses, including applications in wireless communication device handsets and other devices. Any features described as modules or components may be implemented together in an integrated logic device or separately as discrete but interoperable logic devices. If implemented in software, the techniques may be implemented at least in part by a computer-readable data storage medium comprising program code including instructions that, when executed, perform one or more of the methods described above. The computer-readable data storage medium may form part of a computer program product, which may include packaging materials. The computer-readable medium may include memory or a data storage medium, such as Random Access Memory (RAM) (such as Synchronous Dynamic Random Access Memory (SDRAM), read-only memory (ROM), non-volatile random access memory (NVRAM), electrically erasable programmable read-only memory (EEPROM)), flash memory, a magnetic or optical data storage medium, and so forth. Additionally or alternatively, the techniques may be realized at least in part by a computer-readable communication medium that carries or communicates program code, such as a propagated signal or wave, in the form of instructions or data structures and that can be accessed, read, and/or executed by a computer.

The program code may be executed by a processor, which may include one or more processors, such as one or more Digital Signal Processors (DSPs), general purpose microprocessors, Application Specific Integrated Circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Such a processor may be configured to perform any of the techniques described in this disclosure. A general purpose processor may be a microprocessor; but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Thus, the term "processor" as used herein may refer to any of the foregoing structure, any combination of the foregoing structure, or any other structure or device suitable for implementing the techniques described herein. Further, in some aspects, the functions described herein may be provided in dedicated software modules or hardware modules configured for encoding and decoding, or incorporated in a combined video encoder-decoder (CODEC).

Claims (21)

1. A method of encoding video data, comprising:

obtaining video data at an encoding device, wherein for a portion of a video picture of the video data, obtaining video data for the portion of the video picture of the video data comprises:

obtaining parameters describing a function of an uninterrupted, quantization factor, the function being used for dynamic range adjustment of samples in the portion of the video picture, and the quantization factor being associated with quantized transform coefficients used for encoding the portion of the video picture;

generating a syntax structure indicating the parameters describing the function for dynamic range adjustment of the samples; and

generating encoded video data from the video data indicating samples of the portion of the video picture, wherein the syntax structure is included within the encoded video data.

2. The method of claim 1, wherein the function of the quantization factor comprises a logarithmic function of a value derived from the quantization factor.

3. The method of claim 1, wherein the syntax structure is generated to be associated with a sequence of video pictures or the video pictures in a sequence of video pictures.

4. The method of claim 1, wherein the syntax structure comprises syntax elements indicating parameters of the function.

5. The method of claim 4, wherein the syntax structure comprises syntax elements indicating parameters defining a one-dimensional function.

6. The method of claim 1, wherein the syntax structure indicates one or more of a position of the video picture in a sequence of video pictures, an intra period, a random access period, or a sequence of pictures, and wherein obtaining parameters describing the function comprises determining the parameters based on one or more of the position of the video picture in a sequence of video pictures, the intra period, the random access period, or the sequence of pictures.

7. The method of claim 1, further comprising generating a second syntax structure indicating parameters of a second parametric function indicating a chroma Dynamic Range Adjustment (DRA) scaling correction term.

8. The method of claim 7, wherein the second parametric function is a function of a Quantization Parameter (QP) associated with a luma component of the portion of the video picture and an offset associated with the luma component and one or more chroma components of the portion of the video picture.

9. A method of decoding video data, comprising:

determining, from an encoded video bitstream comprising encoded video data, for a portion of a video picture from the encoded video data, a syntax structure comprising parameters describing a function of a quantization factor, the function being uninterrupted for dynamic range adjustment of samples in the portion of the video picture, and wherein the quantization factor is associated with quantized transform coefficients used to encode the portion of the video picture;

decoding the video picture; and

applying the function to samples in the portion of the video picture to perform dynamic range adjustment of samples.

10. The method of claim 9, wherein the function of the quantization factor comprises a logarithmic function of a value derived from the quantization factor.

11. The method of claim 9, further comprising decoding, from the encoded video data, data associating the syntax with a sequence of video pictures or the video pictures in a sequence of video pictures.

12. The method of claim 9, wherein the syntax structure comprises syntax elements indicating parameters of the function.

13. The method of claim 12, wherein the syntax structure comprises syntax elements indicating parameters defining a one-dimensional function.

14. The method of claim 9, wherein the syntax structure indicates one or more of a position of the video picture in a sequence of video pictures, an intra period, a random access period, or a sequence of pictures, and wherein determining parameters describing the function comprises determining the parameters based on one or more of the position of the video picture in a sequence of video pictures, the intra period, the random access period, or the sequence of pictures.

15. The method of claim 9, further comprising: decoding a second syntax structure from the encoded video bitstream that indicates parameters of a second parametric function that indicates a chroma Dynamic Range Adjustment (DRA) scaling correction term; and applying the second parametric function to the sample points.

16. The method of claim 15, wherein the second parametric function is a function of a Quantization Parameter (QP) associated with a luma component of the portion of the video picture and an offset associated with the luma component and one or more chroma components of the portion of the video picture.

17. An apparatus for decoding video data, comprising:

a memory configured to store at least a portion of a video picture; and

a video processor configured to:

determining, from an encoded video bitstream comprising encoded video data, for the portion of the video picture from the encoded video data, a syntax structure comprising parameters describing a function of a quantization factor, the function being an uninterrupted dynamic range adjustment for samples in the portion of the video picture, and wherein the quantization factor is associated with the portion of quantized transform coefficients used to encode the video picture;

decoding the video picture using the encoded video data; and

applying the function to samples in the portion of the video picture to perform dynamic range adjustment of samples.

18. The apparatus of claim 17, wherein the function of the quantization factor comprises a logarithmic function of a value derived from the quantization factor.

19. The apparatus of claim 17, wherein the processor is further configured to decode, from the encoded video data, data that associates the syntax with a video picture sequence or the video pictures in a video picture sequence.

20. The apparatus of claim 17, wherein the syntax structure comprises a syntax element indicating a parameter of the function.

21. The apparatus of claim 20, wherein the syntax structure comprises a syntax element indicating parameters defining a one-dimensional function.

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